In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

Although Cloud computing itself has many open problems, researchers in the field have already made the leap to envision Inter-Cloud computing. Their goal is to achieve better overall Quality of Service QoS, reliability and cost efficiency by utilizing multiple clouds. Inter-Cloud research is still in its infancy, and the body of knowledge in the area has not been well defined yet. In this work, we propose and motivate taxonomies for Inter-Cloud architectures and application brokering mechanisms. We present a detailed survey of the state of the art in terms of both academic and industry developments 20 projects, and we fit each project onto the discussed taxonomies. We discuss how the current Inter-Cloud environments facilitate brokering of distributed applications across clouds considering their nonfunctional requirements. Finally, we analyse the existing works and identify open challenges and trends in the area of Inter-Cloud application brokering. Copyright © 2012 John Wiley & Sons, Ltd.

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Inter-Cloud architectures and application brokering: taxonomy and survey

In the landscape of cloud computing, the competition between providers has led to an ever growing number of cloud solutions offered to consumers. The ability to run and manage multi-cloud systems (i.e., applications on multiple clouds) allows exploiting the peculiarities of each cloud solution and hence optimising the performance, availability, and cost of the applications. However, these cloud solutions are typically heterogeneous and the provided features are often incompatible. This diversity hinders the proper exploitation of the full potential of cloud computing, since it prevents interoperability and promotes vendor lock-in, as well as it increases the complexity of development and administration of multi-cloud systems. This problem needs to be addressed promptly. In this paper, we provide a classification of the state-of-the-art of cloud solutions, and argue for the need for model-driven engineering techniques and methods facilitating the specification of provisioning, deployment, monitoring, and adaptation concerns of multi-cloud systems at design-time and their enactment at run-time.

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Towards Model-Driven Provisioning, Deployment, Monitoring, and Adaptation of Multi-cloud Systems

Vendor lock-in is a major barrier to the adoption of cloud computing, due to the lack of standardization. Current solutions and efforts tackling the vendor lock-in problem are predominantly technology-oriented. Limited studies exist to analyse and highlight the complexity of vendor lock-in problem in the cloud environment. Consequently, most customers are unaware of proprietary standards which inhibit interoperability and portability of applications when taking services from vendors. This paper provides a critical analysis of the vendor lock-in problem, from a business perspective. A survey based on qualitative and quantitative approaches conducted in this study has identified the main risk factors that give rise to lock-in situations. The analysis of our survey of 114 participants shows that, as computing resources migrate from on-premise to the cloud, the vendor lock-in problem is exacerbated. Furthermore, the findings exemplify the importance of interoperability, portability and standards in cloud computing. A number of strategies are proposed on how to avoid and mitigate lock-in risks when migrating to cloud computing. The strategies relate to contracts, selection of vendors that support standardised formats and protocols regarding standard data structures and APIs, developing awareness of commonalities and dependencies among cloud-based solutions. We strongly believe that the implementation of these strategies has a great potential to reduce the risks of vendor lock-in.

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Critical analysis of vendor lock-in and its impact on cloud computing migration: a business perspective

In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.

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Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators willing to choose the Cloud without being strictly bound to a specific solution is mostly neglected. We argue that Model-Driven Development can be helpful in this context as it would allow developers to design software systems in a cloud-agnostic way and to be supported by model transformation techniques into the process of instantiating the system into specific, possibly, multiple Clouds. The MODAClouds (MOdel-Driven Approach for the design and execution of applications on multiple Clouds) approach we present here is based on these principles and aims at supporting system developers and operators in exploiting multiple Clouds for the same system and in migrating (part of) their systems from Cloud to Cloud as needed. MODAClouds offers a quality-driven design, development and operation method and features a Decision Support System to enable risk analysis for the selection of Cloud providers and for the evaluation of the Cloud adoption impact on internal business processes. Furthermore, MODAClouds offers a run-time environment for observing the system under execution and for enabling a feedback loop with the design environment. This allows system developers to react to performance fluctuations and to re-deploy applications on different Clouds on the long term.

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MODAClouds: a model-driven approach for the design and execution of applications on multiple clouds

This books is open access under a CC BY 4.0 license. This book summarizes work being undertaken within the collaborative MODAClouds research project, which aims to facilitate interoperability between heterogeneous Cloud platforms and remove the constraints of deployment, portability, and reversibility for end users of Cloud services. Experts involved in the project provide a clear overview of the MODAClouds approach and explain how it operates in a variety of applications. While the wide spectrum of available Clouds constitutes a vibrant technical environment, many early-stage issues pose specific challenges from a software engineering perspective. MODAClouds will provide methods, a decision support system, and an open source IDE and run-time environment for the high-level design, early prototyping,semiautomatic code generation, and automatic deployment of applications on multiple Clouds. It will free developers from the need to commit to a fixed Cloud technology stack during software design and offer benefits in terms of cost savings, portability of applications and data between Clouds, reversibility (moving applications and data from Cloud to non-Cloud environments), risk management, quality assurance, and flexibility in the development process.

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Model-Driven Development and Operation of Multi-Cloud Applications: The MODAClouds Approach

Data is growing. We are all aware of this in the IT industry, it is a common mantra. The elephant in the room is the ownership of that data and the use of that data. As with many new technologies, its legal and personal implications are not well understood until the technology has matured. Data ownership has by default resided with organisations that hold the data; utility companies, websites, retailers and data aggregators and brokers. If data could be owned by the people it identifies, the data handlers would have to pay to use that data for sales and marketing purposes. We are not suggesting payment would be the mostly illusory free services and hidden discounts that are the current answer but real money or an asset that can be bartered or purchased. If even the poorest people can gain an income this would revolutionise personal finance for those who register on the web either for purchases or to make their name available for use. We propose such a revolution in data ownership and urge all data generators to establish their rights to a business asset that they frequently gift to already wealthy organisations. Don't be a mere generator of data, become a personal data aggregator, collecting and controlling all your data. Time to man the barricades against entities who are using your data for their profit and pleasure, not yours.

Data Is the New Currency

Compliance with the new European General Data Protection Regulation (Regulation (EU) 2016/679, GDPR) and security assurance are currently two major challenges of Cloud-based systems. GDPR compliance implies both privacy and security mechanisms definition, enforcement and control, including evidence collection. This study presents a novel DevOps framework aimed at supporting Cloud consumers in designing, deploying and operating (multi)Cloud systems that include the necessary privacy and security controls for ensuring transparency to end-users, third parties in service provision (if any) and law enforcement authorities. The framework relies on the risk-driven specification at design time of privacy and security level objectives in the system service level agreement and in their continuous monitoring and enforcement at runtime.

Service level agreement-based GDPR compliance and security assurance in(multi)Cloud-based systems

The growth in the number of cloud computing users has led to the availability of a variety of cloud based services provided by different vendors. This has made the task of selecting a suitable set of services quite difficult. There has been a lot of research towards the development of suitable decision support system (DSS) to assist users in making an optimal selection of cloud services. However, existing decision support systems cannot address two crucial issues: firstly, the involvement of both business and technical perspectives in decision making simultaneously and, secondly, the multiple-clouds services based selection using a single DSS. In this paper, we tackle these issues in the light of solving the problem of cloud service discovery. In particular, we present the following novel contributions: Firstly, we present a critical analysis of the state-of-the-art in decision support systems. Based on our analysis, we identify critical shortcomings in the existent tools and develop the set of requirements which should be met by a potential DSS. Secondly, we present a new holistic framework for the development of DSS which allows a pragmatic description of user requirements. Additionally, the data gathering and analysis is studied as an integral part of the proposed DSS and therefore, we present concrete algorithms to assess the data for an optimal service discovery. Thirdly, we assess our framework for applicability to cloud service selection using an industrial case study. We also demonstrate the implementation and performance of our proposed framework using a prototype which serves as a proof of concept. Overall, this paper provides a novel and holistic framework for development of a multiple cloud service discovery based decision support system.

Peter Matthews

Papers

MODAClouds: a model-driven approach for the design and execution of applications on multiple clouds

Model-Driven Development and Operation of Multi-Cloud Applications: The MODAClouds Approach

Data Is the New Currency

Service level agreement-based GDPR compliance and security assurance in(multi)Cloud-based systems

Risk-driven framework for decision support in cloud service selection